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"GeoDec"Constructing an information-rich and realistic 3-dimensional visualizationand simulation of a geographical location, rapidly and accurately.
GeoDec (Geospatial Decision Making) is a collaborative project with Dr. Cyrus Shahabi, Dr. Craig Knoblock , Dr. Ulrich Neumann and Dr. Ramakant Nevatiaunder IMSC to build an information-rich and realistic geospatial space (e.g., a city) with temporal dimension rapidly and accurately, which supports visualization, querying and data analysis capabilities. Recent growth of the geo-spatial information and their availability has motivated the effort to integrate them to support a comprehensive set of queries in different modalities. However due to the inherent difference in data formats available and their different accuracy levels, doing a seamless, consistent and efficient integration of different data sources is a very challenging task.
By utilizing various information integration approaches such as orthoimagery and street maps conflation, vector data and satellite imagery conflation and road network and map fusion, we strive to create intelligent, information-rich and detailed models that incorporate the visual appeal and accuracy of imagery with detailed attribution information in diverse maps and realistic 3-D visualization for geographic locations.
This interdisciplinary work is being performed by researches from various fields such as databases, artificial intelligence, computer graphics and computer vision in a collaborative effort as part of IMSC, the only NSF engineering research center in the area of Multimedia for integration of various technologies under the GeoDec framework.
Our proposed framework is composed of the following components :
Rapid 3-D model construction from
photographs:
This system is designed to
minimize users' interaction by
giving them the option of working
with a single image at a time. At
the same time, by using basic
information such as one side and
one corner of objects identified
by user in a semi-automatic
process, highly complex polygonal
roof shaped buildings can be
modeled.
Here is 3D models of USC campus with photograph texture rendered in VRML:
The 3D models of Downtown Los Angeles
The 3D models of ShangHai Jiao Tong University, China
Texture mapping of buildings and
video fusion:
In a two fold approach, static and dynamics of scenes are captured from a photographic process involving video or numerous still images. Static textures capture the color attributes of buildings and street scenes and then enhanced with video streams to show dynamic aspects of scenes (e.g. movement of cars on other objects mapped on the 3-D model (video fusion).
To see the video demo for the following example, please click here.
Geospatial Data Fusion
The next step is to enhance the model by integrating all sorts of data from both online sources (e.g., yellow pages, property-tax sites, geocoders) as well as private databases (e.g., road vector data, maps, gazetteer points).
Integrating Vector Data and Imagery:
This research is on the problem
of accurate integration of geospatial vector data with (satellite or aerial)
images. One application for such integration could be for the purpose of
automatic recognition and annotation of spatial objects in imagery. We utilized
a wide variety of geospatial and textual data available on the Internet in
order to efficiently and accurately identify objects in the satellite imagery.
To demonstrate the utility of our technique, we built an application that
utilizes the satellite imagery from the Microsoft TerraService and the
Tigerline vector files from US Census Bureau (as well as some online sources)
to annotate buildings on the imagery. Our main challenge is that geospatial
data (specifically, vector and image data) obtained from various data sources
may have different projections, different accuracy levels, and different
inconsistencies. The applications that integrate information from various
geospatial data sources must be able to overcome these inconsistencies
accurately, in real-time and for large regions. Traditionally, this problem has
been in the domain of the image processing and GIS systems. However, the
conflation approach used in various GIS systems to manually or
semi-automatically align two geospatial data sets does not scale up to large
regions.
We utilize a fully automatic
conflation technique to fix the
vector data and image alignment.
Based on the above approach, we
use common vector datasets as
"glue" to further integrate
imagery with maps. This is done by
having a set of control point
pairs for the map and imagery,
using conventional conflation
technique to align the map with
the satellite imagery. Please refer to Geosemble Technologies for more details. Effective Presentation and Querying: We are currently developing a user interface - Negaah- (Negaah in Persian means “viewing”) for GeoDec that will allow the user to navigate and interactively query the 3D environment in real-time. Negaah allows greater decision-making flexibility by allowing the user to query geospatial data based on a user-defined selection area. Negaah will also allow the user to submit queries based on a different time intervals for temporal data (such as object trajectories or stored video streams). The users can selectively query and display different layers of information. Negaah also supports more sophisticated queries such as calculating the shortest path between two points.
Examples of data sources that Negaah can already query include:
The following example shows combined queries of "3D buildings" and "Point of Interests":
Visibility Query: The visibility query color-codes all the areas (including gournd and building facades) that is visible to/from to a query point within a certain range.
Blue: Building facades and grounds that are visible to the query point. Glove-Based User
Interface
We have developed a glove-based user interface for users to navigate these immersive and information-rich three-dimensional environments. Our system interprets user commands based on hand gestures obtained using data gloves and an extended range tracking device. This interface allows the user to navigate and interact with the environment intuitively, particularly when using a large display. In addition, automatic level of detail control displays point data (e.g. building names) on the model when it is contextually relevant to the user, based on the distance of the user from the object. The user can also use the glove-based user interface to view other information integrated with the model such as conflated vector or image data. 
Challenges:
Applications:
Future work:
As
part of our future work we would
like to achieve the following
goals:
Download a copy of GeoDec
Brochure from here.
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web admin: sxing@usc.edu |
